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Remote CI/CD Jobs

Browse remote CI/CD positions — ML pipeline automation, DevOps for AI systems, and deployment engineering roles at AI-first companies.

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Remote worldwide
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MLOps Engineer DevOps for AI CI/CD Platform Engineer ML Automation Engineer Infrastructure Engineer

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Jobs & Projects

Snowflake

Posted 2 weeks ago

Staff Designated Support Engineer

Snowflake

IE-Dublin-WW

staff
Full-time
English
Open job
AlphaSense

Posted 2 weeks ago

Staff QE

AlphaSense

Remote - United States · also open in 1 other location

staff
Full-time
English
$148K – $204K / year
python ci/cd typescript
Open job
Cerebras

Posted 2 weeks ago

AI Inference Core - Senior SDET, Release Integration Testing

Cerebras

Sunnyvale, CA

senior
Full-time
English
python ci/cd kubernetes distributed systems
Open job
Databricks

Posted 2 weeks ago

Senior Forward Deployed Engineer, Sr FDE (L5)

Databricks

Remote - India

senior
Full-time
English
Open job
HiddenLayer

Posted 2 weeks ago

Platform Engineer

HiddenLayer

Remote- US

Full-time
English
Open job
Wayve

Posted 2 weeks ago

Test Engineer

Wayve

Leonberg, Germany

Full-time
English
Open job
Wayve

Posted 2 weeks ago

Cyber Security Engineer

Wayve

Leonberg, Germany

Full-time
English
Open job
Astronomer
Full-time
English
Open job
Snowflake
staff
Full-time
English
$236K – $339K / year
Open job
Airbyte

Posted 2 weeks ago

Technical Support Engineer

Airbyte

Canada

Full-time
English
C$89K – C$105K / year
Open job

Role guide

What to expect in remote CI/CD jobs

CI/CD for AI is more complex than standard software — it requires validating not just code, but data, models, and system behaviour. Remote CI/CD jobs at AI companies involve building automated testing and deployment pipelines for ML systems, implementing model regression testing, and ensuring AI products ship reliably. Engineers who bridge DevOps and ML system knowledge are in consistent demand.

What you'll work on

  • Build automated ML testing pipelines that prevent broken models reaching production
  • Design deployment workflows that ship AI updates in minutes, not days
  • Implement shadow mode testing to safely validate new model versions on live traffic
  • Create infrastructure-as-code environments for reproducible AI development

What companies look for

  • CI/CD platform experience — GitHub Actions, GitLab CI, CircleCI, or Jenkins
  • ML-specific testing — data validation, model regression, integration testing
  • Blue/green and canary deployment strategies for safe ML model releases

Frequently asked questions

What remote CI/CD jobs are available at AI companies?

MLOps and DevOps engineering roles where CI/CD for ML systems is a core responsibility. Most require Docker and cloud platform experience (AWS, GCP, or Azure) alongside CI/CD pipeline knowledge.

What makes CI/CD for ML different from regular software CI/CD?

ML pipelines must validate data quality, model performance metrics, and integration behaviour — not just code correctness. Engineers design test suites that catch data drift, model degradation, and integration failures automatically.

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